• Journal of Korea Entertainment Industry Association
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• v.13 no.4
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• pp.271-281
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• 2019

The purpose of this study is to provide basic data for improving the adaptability of college life by examining the effects of individuality and relationship of university freshmen on college life adaptation. The study subjects were 383 freshmen enrolled in a university in Chungbuk C City, and a multiple regression analysis was conducted to examine the factors of impact. The first study found that boys were more individual in genders, depending on the general characteristics. Extroverted students were more relational. In the majors, students in the humanities and social sciences were more related, and students in the natural engineering department were more individual. Second, the lower factors affecting college students' adaptation to college life were found to be autonomous in individuality, and affinity and intimacy in relation. In particular, autonomy has the greatest impact on adaptation to college life, followed by affinity and intimacy. Based on these results, policy suggestions are needed first, it is necessary to balance and balance individuality and relationship. second, it is necessary to create activities and learning environments that you can choose for yourself. third, it is necessary to develop programs to promote affinity and intimacy such as department events and club activities. fourth, emotional and psychological program support through face-to-face contact should be activated to improve individuality and relationship.

• Journal of Korean Elementary Science Education
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• v.42 no.1
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• pp.149-160
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• 2023

A Korean-version science curiosity questionnaire (Science Curiosity in Learning Environments [SCILE(15)]) was developed after factor analysis of the Korean-version SCILE(30) questionnaire. Pre-service elementary school teachers were surveyed using the Korean-version SCILE(30), and a factor analysis based on their responses was performed. The factor analysis demonstrated that the Korean-version SCILE(15) consisted of three curiosity factors: a 'science practices' factor, a 'stretching' factor, and an 'embracing' factor. Confirmatory factor analysis of the factor structure revealed correlations between all the factors, thus confirming their commonality as a science curiosity factors. The Cronbach alpha for the reliability of all items in the Korean-version SCILE(15) and of items by factor was greater than 0.700. The Korean-version SCILE(15) was therefore evaluated to be reliable as a science curiosity questionnaire. Pre-service elementary teachers who participated in the survey for the development of the SCILE(15) were aware of the 'science practices', 'stretching', and 'embracing' science curiosity factors. Analysis in a general linear model of the degree of recognition accorded by pre-service elementary teachers to the three science curiosity factors demonstrated significant differences between the curiosity factors in terms of recognition. This cohort of pre-service elementary teachers showed the highest level of recognition of the 'stretching' curiosity factor and the lowest level of recognition of the 'embracing' curiosity factor.

• Journal of the Korean Society of Marine Environment & Safety
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• v.29 no.1
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• pp.24-35
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• 2023

Rapid industrialization and urbanization have led to severe marine pollution. A Water Quality Index (WQI) has been developed to allow the effective management of marine pollution. However, the WQI suffers from problems with loss of information due to the complex calculations involved, changes in standards, calculation errors by practitioners, and statistical errors. Consequently, research on the use of artificial intelligence techniques to predict the marine and coastal WQI is being conducted both locally and internationally. In this study, six techniques (RF, XGBoost, KNN, Ext, SVM, and LR) were studied using marine environmental measurement data (2000-2020) to determine the most appropriate artificial intelligence technique to estimate the WOI of five ecoregions in the Korean seas. Our results show that the random forest method offers the best performance as compared to the other methods studied. The residual analysis of the WQI predicted score and actual score using the random forest method shows that the temporal and spatial prediction performance was exceptional for all ecoregions. In conclusion, the RF model of WQI prediction developed in this study is considered to be applicable to Korean seas with high accuracy.

• The Journal of the Korea institute of electronic communication sciences
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• v.17 no.2
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• pp.343-350
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• 2022

It is worth verifying the effectiveness of data integration between data with different features. This study investigated whether the data integration affects the accuracy of deep neural network (DNN), and which integration method shows the best improvement. This study used two different public datasets. One public dataset was taken in an actual farm in India. And another was taken in a laboratory environment in Korea. Leaf images were selected from two different public datasets to have five classes which includes normal and four different types of plant diseases. DNN used pre-trained VGG16 as a feature extractor and multi-layer perceptron as a classifier. Data were integrated into three different ways to be used for the training process. DNN was trained in a supervised manner via the integrated data. The trained DNN was evaluated by using a test dataset taken in an actual farm. DNN shows the best accuracy for the test dataset when DNN was first trained by images taken in the laboratory environment and then trained by images taken in the actual farm. The results show that data integration between plant images taken in a different environment helps improve the performance of deep neural networks. And the results also confirmed that independent use of plant images taken in different environments during the training process is more effective in improving the performance of DNN.

• 한국노년학
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• v.29 no.2
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• pp.669-682
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• 2009

The purpose of this study was to explore the role of professional identity as mediating variable in the relationship between job- and organization- related factors and job satisfaction. This study surveyed social workers who worked at 24 senior welfare facilities in Daegu·Gyeoungbuk province from Aug. 1. to Aug. 30. 2006. A total of 137 questionnaires were collected using on-site survey (response rate 76.7%). Statistical analyses were performed using SPSS 12.0 for Windows. Descriptive analysis and frequency analysis were performed on overall measurement items and hierarchical regression analysis was conducted to test the mediating effect of professional identity. The reliability of statements was acceptable since the coefficient alphas were > .70. Results of hierarchical regression showed that professional identity was verified as a partial mediator in the relationship between factors related with job and organization and job satisfaction. As the population ages, there will be an increasing need for professional social workers effectively to work with and help care for the elderly. This study highlighted that job- and organization- related factors, namely self-regulations and social supports, are significantly related with job satisfaction of social workers. Especially, such effect was more significantly apparent in high professional identity which is playing a partial mediator. This result implies that there is potential to change work environments of social workers ensuring a delegation of power and responsibility. Therefore, efforts should be made to improve the promotion system and connect social worker as servant with community through diverse service learning programs.

• Korean Journal of Culture and Social Issue
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• v.14 no.1_spc
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• pp.319-348
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• 2008

Self-efficacy, achievement goals, task value, and attribution are some of the representative motivation constructs that explain adolescents' cognition, affect, and behavioral patterns in achievement settings. These constructs have won researchers' recognition by demonstrating explanatory and predictive utility that transcends various social and cultural milieus learners are exposed to. Korean adolescents' motivation is generally in line with this universal trend and can be described adequately with these constructs. Nonetheless, there also exist a host of indigenous factors that shape these motivation constructs to be uniquely Korean. The purpose of the present article was to explore some of the socio-cultural factors that appear to wield particularly determining effects on Korean adolescents' academic motivation. Review of the relevant literature identified interdependent self-construal, traditional morals of filial piety, familism, educational fervor, academic elitism, and the college entrance system as important cultural, social, and policy-related such factors. Also discussed in this article were the roles of these factors in creating more immediate psychological learning environments for Korean adolescents, such as parent-child relationships, teacher-student relationships, and classroom goal structures.

• KIPS Transactions on Software and Data Engineering
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• v.12 no.10
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• pp.445-454
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• 2023

Recently, various fault diagnosis studies are being conducted utilizing data from collaborative robots. Existing studies performing fault diagnosis on collaborative robots use static data collected based on the assumed operation of predefined devices. Therefore, the fault diagnosis model has a limitation of increasing dependency on the learned data patterns. Additionally, there is a limitation in that a diagnosis reflecting the characteristics of collaborative robots operating with multiple joints could not be conducted due to experiments using a single motor. This paper proposes an LSTM diagnostic model that can overcome these two limitations. The proposed method selects representative normal patterns using the correlation analysis of vibration and current data in single-axis and multi-axis work environments, and generates residual patterns through differences from the normal representative patterns. An LSTM model that can perform gear wear diagnosis for each axis is created using the generated residual patterns as inputs. This fault diagnosis model can not only reduce the dependence on the model's learning data patterns through representative patterns for each operation, but also diagnose faults occurring during multi-axis operation. Finally, reflecting both internal and external data characteristics, the fault diagnosis performance was improved, showing a high diagnostic performance of 98.57%.

• Journal of The Korean Association For Science Education
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• v.44 no.3
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• pp.273-299
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• 2024

This is a qualitative research study in which three families focused on scientific culture and conducted the process of forming a family fandom using ethnography. The ultimate goal of science education is the "cultivation of scientifically literate persons.", The researcher examines families who regularly participate in informal science educational programs, such as those offered by the National Marine Biodiversity Institute of Korea, to understand the cultural ans sociological significance of these activities as part of their daily routines. This study analyzes and summarizes the experiences of three families in different home environments as to the completion of the family fandom through the process of self-sustaining cultural practice formation through family education activities, and science activities. This study found that the process tword completion is more meaningful than the completion itself, in the context of science, culture, family and fandom. The findings of this study are as follows: 1) The process of forming a family fandom began with the individual purpose of each family member. 2) The process of fandom formation was created in an organic relationship through the interaction between parents and children, and the self-sustaining cultural practice strengthened the bond and expanded the consensus on scientific culture. 3) Parents and children together share scientific culture, and unique culture in the form of sharing in their own cultural life as becoming scientifically literate people. The self-sustaining cultural practice of selecting and enjoying these scientific activities is not simple consumption of popular culture, but the role of parents as cultural designers. This has conducted experiential consumption as "refined (or sophisticated) cultural consumers," and family leisure activities as meaning production of family members so it has social and cultural implications that can be developed into a scientific culture.

• The Transactions of the Korea Information Processing Society
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• v.13 no.4
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• pp.199-207
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• 2024

Local reservoirs are crucial sources for agricultural water supply, necessitating stable water level management to prepare for extreme climate conditions such as droughts. Water level prediction is significantly influenced by local climate characteristics, such as localized rainfall, as well as seasonal factors including cropping times, making it essential to understand the correlation between input and output data as much as selecting an appropriate prediction model. In this study, extensive multivariate data from over 400 reservoirs in Jeollabuk-do from 1991 to 2022 was utilized to train and validate a water level prediction model that comprehensively reflects the complex hydrological and climatological environmental factors of each reservoir, and to analyze the impact of each input feature on the prediction performance of water levels. Instead of focusing on improvements in water level performance through neural network structures, the study adopts a basic Feedforward Neural Network composed of fully connected layers, batch normalization, dropout, and activation functions, focusing on the correlation between multivariate input data and prediction performance. Additionally, most existing studies only present short-term prediction performance on a daily basis, which is not suitable for practical environments that require medium to long-term predictions, such as 10 days or a month. Therefore, this study measured the water level prediction performance up to one month ahead through a recursive method that uses daily prediction values as the next input. The experiment identified performance changes according to the prediction period and analyzed the impact of each input feature on the overall performance based on an Ablation study.

• Smart Media Journal
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• v.12 no.11
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• pp.48-56
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• 2023

The technology of Three-dimensional human posture estimation is used in sports, motion recognition, and special effects of video media. Among various methods for this, multi-view 3D human pose estimation is essential for precise estimation even in complex real-world environments. But Existing models for multi-view 3D human posture estimation have the disadvantage of high order of time complexity as they use 3D feature maps. This paper proposes a method to extend an existing monocular viewpoint multi-frame model based on Transformer with lower time complexity to 3D human posture estimation for multi-viewpoints. To expand to multi-viewpoints our proposed method first generates an 8-dimensional joint coordinate that connects 2-dimensional joint coordinates for 17 joints at 4-vieiwpoints acquired using the 2-dimensional human posture detector, CPN(Cascaded Pyramid Network). This paper then converts them into 17×32 data with patch embedding, and enters the data into a transformer model, finally. Consequently, the MLP(Multi-Layer Perceptron) block that outputs the 3D-human posture simultaneously updates the 3D human posture estimation for 4-viewpoints at every iteration. Compared to Zheng[5]'s method the number of model parameters of the proposed method was 48.9%, MPJPE(Mean Per Joint Position Error) was reduced by 20.6 mm (43.8%) and the average learning time per epoch was more than 20 times faster.